## Long Tail Distribution

Imagine you are in a room of 30 people. If we were to calculate an average monthly income of all of you, we would get \$2,000, for example. Now imagine that Bill Gates has just walked in in the room. What is going to happen if we calculate the average income now? The number we'll get will have no sense because it will not show the real picture of the sample. This is why we need to take the possibility of extraordinary events happening in non-linear systems into consideration. The long tail distribution graph refers to those extraordinary events, also known as black swan events.

You can find a lot of information about the effect of black swan events and even the ways of predicting them. However, the idea of this type of event is that it is so stunning and unexpected that it's almost impossible to assume its probability as it's incredibly low. Some of the examples of the long tail distribution seen in our history are the sinking of Titanic in 1912, Fukushima nuclear disaster, 9/11. All of this situations caused shock as it was hard to believe they actually happened. Statistically speaking, none of them would have been present on a normal distribution graph.